1. Field of the Invention
The present invention relates generally to an image forming apparatus having a self-diagnosis system. More particularly, the present invention relates to an image forming apparatus so adapted that it can make self-diagnosis of the operating state and the like utilizing artificial intelligence and knowledge engineering which have been being extensively studied in recent years.
2. Description of the Prior Art
In the development field of precision instruments, industrial machines and the like, expert systems utilizing artificial intelligence (so-called AI) techniques have been studied extensively in recent years for the purpose of realizing labor saving in maintenance work and long-term automatic operation. The expert systems include one for making self-diagnosis to judge whether or not an apparatus develops a fault and making self-repair of the fault developed by the apparatus.
However, the conventional expert system (an automatic control system and a fault diagnosis system) only basically operates an actuator corresponding to a sensor on the basis of an output of the sensor. Accordingly, it is not complete as a Self-Maintenance Machine (SMM).
Therefore, the applicant of the present application found a machine control method using diagnosis-repair reasoning on an object model based on qualitative physics and invented a new self-diagnosis and self-maintenance system for an image forming apparatus utilizing such a machine control method, to file a patent application (see, for example, Japanese Patent Laid-Open Gazette No. 130459/1992).
The self-diagnosis and self-maintenance system for an image forming apparatus according to the prior application has the following features:
(1) Detected values of sensors provided for an objective machine (an image forming apparatus) are converted into qualitative values and are used for control.
(2) The structure and the properties of the image forming apparatus are qualitatively expressed using a casual relation network of parameters (a parameter model) representing the property of the image forming apparatus.
(3) The qualitative values obtained by converting the values of the sensors are applied to the parameter model to make qualitative simulation for fault diagnosis and fault repair reasoning.
Specifically, fault diagnosis and fault repair based on the Qualitative Model based System (QMS) are made.
In the self-diagnosis and self-maintenance system according to the prior application of the applicant having such features, even if the image forming apparatus develops a fault accompanied by, for example, the change in structure, the fault can be flexibly coped with. The reason for this is that it is possible to dynamically change a control point and a control loop of the objective machine by utilizing the qualitative simulation.
In the above described self-diagnosis and self-maintenance system according to the prior application, however, there is a possibility that in converting detected values of sensors into qualitative values, errors occur in the conversion. The reason for this is that when the detected value of each of the sensors is converted into the qualitative value, a landmark is defined in a qualitative quantity space, and the detected value is converted into the qualitative value which differs depending on whether the detected value is larger or smaller than the landmark. Accordingly, the landmark must be correctly defined.
However, this landmark may, in some cases, be changed depending on, for example, the environment in which the image forming apparatus is used. In addition, there is a possibility that the detected value of the sensor itself is not necessarily a correct value depending on, for example, the limit of the measurement precision of the sensor.
In the conventional system, therefore, the conversion of the detected value of the sensor into the qualitative value which forms the basis for control varies. As a result, accurate qualitative simulation cannot be made, so that there is a possibility that errors occur in fault diagnosis and fault repair.
Furthermore, it cannot be said that the operation of the above described self-diagnosis and self-maintenance system according to the prior application as a practical machine built-in system is the most suitable in that the scale of the system is large and the speed of execution is low. Therefore, it is desired to decrease the size and increase the speed of the self-diagnosis and self-maintenance system.